EPiC Series in Health Sciences最新文献

{"title":"Towards Automatic Generation of Patient-Specific Knee Models","authors":"E. Elyasi, M. Bucki, Boubaker Asaadi, D. Elizondo, A. Perrier","doi":"10.29007/5r88","DOIUrl":"https://doi.org/10.29007/5r88","url":null,"abstract":"The objective of the current paper is to present a pipeline designed to reduce the pre-processing time required to build subject-specific finite element knee models and facilitate their clinical integration. The pipeline involves development and validation of an atlas model of the knee joint and features of the TwInsight software suit that use novel methodologies such as: 1) deep learning for automatic segmentation of the bones from computed tomography scans, 2) automatic generation of finite element meshes with hexahedral elements, and 3) anatomical inference algorithm to adapt the atlas model to the morphology of a subject and result in the subject’s personalized biomechanical model.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131033544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tibial and femoral bones segmentation on CT-scans: a deep learning approach","authors":"Ludivine Maintier, Ehouarn Maguet, A. Clavé, E. Stindel, V. Burdin, G. Dardenne","doi":"10.29007/6jqc","DOIUrl":"https://doi.org/10.29007/6jqc","url":null,"abstract":"Custom implants in Total Knee Arthroplasty (TKA) could improve prosthesis’ durability and patient’s comfort, but designing such personalized implants requires a simplified and thus automatic workflow to be easily integrated in the clinical routine. A good knowledge of the shape of the patient's femur and tibia is necessary to design it, but segmentation is still today a key issue. We present here an automatic segmentation approach of the three joints of the lower limb: hip, knee and ankle, using convolutional neural networks (CNNs) on successive transverse views from CT images. Our three 2D CNNs are built on the U-net model, and their specialization each on one joint allowed us to achieve promising results presented here. This could be integrated in a TKA planning software allowing the automatic design of TKA custom implants.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116214253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ability to Achieve Mediolateral Gap Balance with Instrumented Navigated Total Knee Arthroplasty – A Review of the First 150 Cases","authors":"L. Angibaud, A. Jung, C. Hamad, Wen Fan, M. Davis, Brian J Zirgibel, Jake Deister, J. Huddleston","doi":"10.29007/d37h","DOIUrl":"https://doi.org/10.29007/d37h","url":null,"abstract":"Appropriate management of the soft tissue envelope at the time of the surgery is critical to the long- term success of total knee arthroplasty (TKA). In this regard, thiscomputer-assisted orthopedic surgery (a force-controlled intraarticular distractor. The first 150 cases performed by 16 surgeons were reported without any exclusions, and for each of these cases, the final mediolateral (ML) laxity was compared to the predicted ML laxity. The average signed ML laxity was well aligned with a neutral differential throughout the full arc of motion and ranged from -0.05mm at 35° of flexion to 0.37mm at 85° of flexion. The signed ML laxity curves tend to be surgeon specific. The average unsigned ML laxity was linear throughout the full arc motion and ranged from 1.14mm at 85° of flexion to 1.27mmat 30° of flexion.the targeted ML gap balance when using afeaturingDespite data from all the users (not only design surgeons) involved with this pilotrelease were considered and the learning curve cases were not excluded, it was observed a high abilitystudy evaluated the ability to achieveCAOS) systemto achieve the targeted ML laxity using the proposed method.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122151022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preoperative planning in shoulder arthroplasty: what about the soft tissue?","authors":"J. Werthel, F. Boux de Casson, Cédric Manelli, J. Chaoui, G. Walch, V. Burdin","doi":"10.29007/x1n7","DOIUrl":"https://doi.org/10.29007/x1n7","url":null,"abstract":"The primary objective of this study was to obtain a reliable method of automatic segmentation of shoulder muscles. The secondary objective of this study was to define a new computed tomography (CT)-based quantitative 3-dimensional (3D) measure of muscle loss (3DML) based on the rationale of the 2-dimensional (2D) qualitative Goutallier score. 102 CT scans were manually segmented and an algorithm of automated segmentation of the muscles was created. The volume of muscle fibers without intramuscular fat was then calculated for each rotator cuff muscle and normalized to the patient's scapular volume to account for the effect of body size (NVfibers). 3D muscle mass (3DMM) was calculated by dividing the NVfibers value of a given muscle by the mean expected volume in healthy shoulders. 3D muscle loss (3DML) was defined as 1 - (3DMM). Automated segmentation of the muscles was possible with a mean Dice of 0.904 ± 0.01 for the deltoid, 0.887 ± 0.014 for the infraspinatus (ISP), 0.892 ± 0.008 for the subscapularis (SSC), 0.885 for the supraspinatus (SSP) and 0.796 ± 0.006 for the teres minor (TM). The mean values of 3DFI and 3DML were 0.9% and 5.3% for Goutallier 0, 2.9% and 25.6% for Goutallier 1, 11.4% and 49.5% for Goutallier 2, 20.7% and 59.7% for Goutallier 3, and 29.3% and 70.2% for Goutallier 4, respectively. 3DML measurements obtained automatically incorporate both atrophy and fatty infiltration, thus they could become a very reliable index for assessing shoulder muscle function which could help in the decision process in shoulder surgery","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129055690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer and Robotic Assisted Orthopaedic Knee Arthroplasty Surgery: Did CAOS technologies have an impact on the mainstream principles and concepts in the orthopaedic knee forum? A case study on alignment and balancing for TKA.","authors":"D. Wallace, F. Mahmood, A. Deakin, P. Riches, K. Deep, J. Baines, F. Picard","doi":"10.29007/h7k4","DOIUrl":"https://doi.org/10.29007/h7k4","url":null,"abstract":"Computer technology is ubiquitous and relied upon in virtually all professional activities. Confounding this is orthopaedic surgery where less than 5% of surgeons are using computer-assisted technologies routinely. However, the impact of Computer Assisted Orthopaedic Surgery (CAOS) may go beyond adoption in theatre.We searched pubmed for all knee arthroplasty papers concerning knee alignment and balancing between 1976 and 2016, dividing the results into those related to CAOS and those not. Results were grouped by technology.Between 2001 and 2008, the number of publications regarding knee navigation multiplied by 20 mainly focused on this topic of alignment and balancing, with alignment papers paralleled between navigation and non-navigation until 2010. After 2010, when navigation publications decline the number of articles related to the knee alignment and balancing without navigation increased granting the value of assessing accurately intraoperative kinematic data to improve Total Knee Arthroplasty (TKA) outcomes. From 2008, patient specific instrumentation (PSI) publications greatly increase, but navigation decreases, while robotic publications rise from 2014.CAOS surgery publications on the search topic of alignment and balancing increased greatly between 2001 and 2018 which may suggest the impact of CAOS technology on this important knee orthopaedic forum segment.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126764302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer and Robotic Assisted Orthopaedic Knee Arthroplasty Surgery Who drives innovations?","authors":"D. Wallace, F. Mahmood, A. Deakin, P. Riches, K. Deep, J. Baines, F. Picard","doi":"10.29007/xn1l","DOIUrl":"https://doi.org/10.29007/xn1l","url":null,"abstract":"Computer assisted and Robotic technology in orthopaedic surgery is still not commonplace compared to un-assisted, conventional orthopaedic surgery. We analysed the relationship between patents and publications trend and question whether we could recognise a pattern which would confirm industry-driven innovation in orthopaedic surgery.Following the same methodology used by Dalton et al. in 2016, we searched pubmed for publications between 1980 and 2018 concerning unicompartmental, patient specific instrumentation, navigation and robotic knee arthroplasty, and patents registered under the “knee arthroplasty” or “knee replacement” label over the same period. Data was plotted using 4 point moving averages.Between 2004 and 2008, the number of publications regarding navigation multiplied by 20 following the number of patents registered during the same period. From 2008 onwards, the number of navigation publications declined while Patient Specific Instrumentation (PSI) publications increased also following patent investments from orthopaedic companies. Finally, robotic publications grew significantly pulled by massive patent registrations after 2012.It seems that the industry has finally found a lucrative economical model after many years of trial and errors and sustained driving innovations.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"6 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120824022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Portable Upper Limb Muscle Dynamometer for Assessment of Neuromuscular Injury Patients","authors":"Colin Day, Erik Bedard, Yassine El Alaoui, Mark Hwang, Michael Berger, J. Giles","doi":"10.29007/k9ms","DOIUrl":"https://doi.org/10.29007/k9ms","url":null,"abstract":"IntroductionPatient recovery from neuromuscular injuries that cause upper limb dysfunction is commonly assessed via manual methods. Manual muscle testing is subjective, time consuming and requires extensive training. Existing dynamometers are more objective, but they are prohibitively expensive and impractically large, making them inaccessible to most clinics and patients with disabilities. Our aim is to develop a table-top upper limb muscle dynamometer that provides standard positioning, ease of use and portability while giving clinicians consistent and reliable quantitative data on a patient’s isotonic and isometric muscle power and strength, respectively.MethodsThe device consists of a lever arm, a brushless DC motor, a load sensor and an ergonomic cuff. It outputs analog data via standard BNC connectors. The device can be intuitively controlled by the operator to test various upper limb joints and motions. Isometric measurement repeatability was assessed by recording the maximal voluntary contractions of 18 healthy participants over three trials.ResultsThe repeatability across 3 trials was 2.70±2.27 Nm (95th percentile: 6.74 Nm) for elbow flexion, and 2.83±2.13 Nm (95th percentile: 5.65 Nm) for elbow extension.ConclusionsThe dynamometer demonstrates a marked improvement in repeatability relative to manual muscle testing. Its small footprint and low cost can make it an easily accessible, standardized testing tool that requires little training to use. Future research and development will focus on using field-oriented control to measure isotonic muscle power in addition to isometric strength.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131286874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cloud-Based Three-Dimensional Pattern Analysis and Classification of Proximal Humeral Fractures – A Feasibility Study","authors":"D. Baumann, Ariane Gerber Popp, Markus Degen, D. Brodbeck, F. Coigny, T. Suter, E. Schkommodau","doi":"10.29007/bprl","DOIUrl":"https://doi.org/10.29007/bprl","url":null,"abstract":"For the complex clinical issue of treatment decision for proximal humeral fractures, dedicated software based on three-dimensional (3D) computer tomography (CT) models would potentially allow for a more accurate fracture classification and help to plan the surgical strategy needed to reduce the fracture in the operating theatre. The aim of this study was to elaborate the feasibility of implementation of such software using state-of-the-art cloud technology to enable access to its functionalities in a distributed manner. Feasibility was studied by implementation of a prototype application, which was tested in a usability study with five biomedical engineers.Implementation of a cloud-based solution was feasible using state-of-the-art technology under application of a specific software architectural approach allowing to distribute computational load between client and server. Mean System Usability Scale (SUS) Score for the developed application was determined to be 63 (StDev 20.4). These results can be interpreted as a medium low usability with high standard deviation of the measured SUS score. We conclude that more test subjects should be included in future studies and the developed application should be evaluated with a representative user group such as orthopaedic shoulder surgeons in a clinical setting.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115666700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intraarticular Quasi-Constant Force Tension in Total Knee Arthroplasty Regardless of Joint Gap and Knee Size","authors":"M. Rueff, Josh Glenboski, Roger Lacaille, L. Angibaud","doi":"10.29007/9217","DOIUrl":"https://doi.org/10.29007/9217","url":null,"abstract":"Balancing soft tissues in the knee with the patella in place and with regularly applied force helps surgeons make decisions for positioning knee components in a manner that is friendly to soft tissues. A novel intraarticular device has been developed for achieving a balanced knee joint over the range of motion of the knee without requiring manual adjustments during surgery. Quasi-Constant force output was generated by the device at usual joint gaps for the knee sizes encountered during total knee arthroplasty.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130545718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic method for computing radiographic parameters of radial metaphyseal fractures in radiographs for surgical decision support","authors":"Avigail Suna, A. Davidson, Leo Joskowicz, Y. Weil","doi":"10.29007/phsh","DOIUrl":"https://doi.org/10.29007/phsh","url":null,"abstract":"PurposeDistal radius fractures (DRF) are common types of fractures with a high incident rate. DRF can be treated either by cast or surgery. To determine the clinical procedure and the operative management, standardized guidelines have become increasingly common. As operative indications are controversial, radiographic parameters (RPs) can provide objective support for effective decision making. Calculating the RPs manually from radiographs is time consuming and subject to observer variability and clinician experience. Our aim was to develop an automatic method for accurately and reliably computing 10 RPs associated with DRF in anteroposterior (AP) and lateral radiographs of a fractured hand with and without cast.MethodsThe inputs are the AP and lateral radiographs of the fractured hand with or without cast. The outputs are 10 RP values and composite images showing the landmark points and axes used in the RPs computation on the radiographs. Our method comprises three main steps: 1) segmentation of the radius and the ulna with a deep learning radiograph pixel classifier; 2) landmark points and axis extraction from the segmentations using geometric model-based methods; 3) RPs computation from the landmarks and generation of composite images. Our study tested the accuracy of step 2.The dataset consists of 20 pairs of AP and lateral radiographs. Ground truth radius and ulna segmentations were manually performed by an expert clinician co-author. Ground truth landmarks were manually located and annotated by the two expert clinician co-authors. The computed RP was considered accurate (in range) when its value was inside the inter and intra observer variability range of the manual annotation. The overall accuracy of the AP and lateral measurements was obtained by averaging the accuracy of each RP.ResultsThe accuracy of the computed AP RPs is 92.7%. The Radial Length and Radial Shift are within the observer variability range; for the Radial Angle, Ulnar Variance and Step all cases are within range except for one outlier; the Gap has two outlier cases. The accuracy of the computed lateral RPs is 100%: all four Palmer Tilt, Dorsal Shift, Gap, and Step are within the clinician observer variability.ConclusionAutomatic computation of distal radius fractures RPs from AP and lateral radiographs of hands with and without cast can be performed accurately. Precise and consistent measurement of RPs may improve the clinical decision making process.","PeriodicalId":385854,"journal":{"name":"EPiC Series in Health Sciences","volume":"79 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133878819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}